Population

Population Change

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Demographics and Population Datasets Involving 34741 ZIP Code

Contains resident demographic data at a summary level as of January 1, 2019. The Resident Data Book is compiled to serve as an information source for queries involving resident demographic as well as a source of data for internal analysis. Statistics are compiled via HUD mandated annual income reviews involving NYCHA Staff and residents. Data is then aggregated and compiled by development. Each record pertains to a single public housing development.

This is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. This dataset is at the county level. The Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. All PQIs apply only to adult populations (over the age of 18 years). The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

This dataset is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

This report provides a weekly summary of deaths with coronavirus disease 2019 (COVID-19) by select geographic and demographic variables. In this release, counts of deaths are provided by the race and Hispanic origin of the decedent. Topics will be added to the release as they become available. These provisional counts are based on a current flow of mortality data in the National Vital Statistics System. National provisional counts include deaths occurring within the 50 states and the District of Columbia that have been received and coded as of the date specified. Data shown on this page may be incomplete and will likely not include all deaths that occurred during a given time period, especially for the more recent time periods. Data on this page are revised weekly and may increase or decrease as new and updated death certificate data are received from the states by NCHS. COVID-19 death counts shown here may differ from other published sources, as data currently are lagged by an average of 1–2 weeks. Weighted population distributions more accurately reflect race/ethnic distributions of the geographic locations where COVID outbreaks are occurring (see below for the methods used to calculate weighted percentages). The weighted population distributions ensure that the population estimates and percentages of COVID-19 deaths represent comparable geographic areas, in order to provide information about whether certain racial and ethnic subgroups are experiencing a disproportionate burden of COVID-19 mortality. See Table 2 below for unweighted populations. Estimated distributions of COVID-19 deaths and population size by race and Hispanic origin The percentages of COVID-19 deaths by race and Hispanic origin were calculated by dividing the number of COVID-19 deaths for each race and Hispanic origin group by the total number of COVID-19 deaths. Percentages may not sum to 100 due to rounding. The distribution of deaths involving COVID-19 by race/ethnicity should not be compared to the race/ethnicity distribution of the U.S. population because COVID-19 deaths are concentrated in certain geographic locations where the racial and ethnic population distribution differs from that of the United States overall. Additionally, COVID-19 deaths are concentrated in certain areas within states, and it is therefore not appropriate to compare the percent of COVID-19 deaths by race/ethnicity to the racial/ethnic population distribution of a given state. To make the estimated population distribution more comparable to the geographic areas where COVID-19 deaths are occurring, weighted population distributions are provided in this report. The weighted population distributions were calculated as follows. County-level population counts by race and Hispanic origin were multiplied by the corresponding total count of COVID-19 deaths by county (of residence). These weighted counts were then summed to the state (or national) level. The percentage of the population within each race and Hispanic origin group by state (or for the U.S.) was then estimated using these weighted counts. Counties with no COVID-19 deaths received a weight of zero, and thus do not contribute to the weighted population totals. Population counts for counties with large numbers of COVID-19 deaths are upweighted proportional to their numbers of COVID-19 deaths. These weighted population distributions ensure that the population estimates and percentages of COVID-19 deaths represent comparable geographic areas, in order to provide information about whether certain racial and ethnic subgroups are experiencing a disproportionate burden of COVID-19 mortality. For example, assume that 75% of the total number of COVID deaths occurred in a single county, County X, while the other 25% of COVID deaths occurred in County Y, and all other counties reported zero deaths. The weighted population counts for County X would contribute 75% of the total population counts, while the population counts for Count

The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.

The datasets contain number of Medicaid PQI hospitalizations (numerator), county Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) for Medicaid enrollees beginning in 2011.

Census data are frequently used throughout Vital Signs as denominators for normalizing many other indicators and rates. The socioeconomic and demographic indicators are grouped into the following categories: population, race/ethnicity, age, households, and income and poverty.

The datasets contain number of Medicaid PDI hospitalizations (numerator), county or zip Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) for Medicaid enrollees beginning in 2011. The Agency for Healthcare Research and Quality (AHRQ) Pediatric Quality Indicators (PDIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. Both the Urinary Tract Infection and Gastroenteritis PDIs include admissions for patients aged 3 months through 17 years. The asthma PDI includes admissions for patients aged 2 through 17 years. Eligible admissions for the Diabetes Short-term Complications PDI includes admissions for patients aged 6 through 17 years.